Artificial intelligence is poised to transform the way we work, both in ways we’ve long imagined, and in ways we can’t. Because AI and machine learning are emerging technologies, the talent that knows how to build and use them is currently in short supply. Compounding that problem, Cade Metz writes at Wired, is that large corporations with massive war chests are acquiring AI startups left and right, hiring up all the top talent and leaving none left for the little guy:
Not everyone can go out and grab thirty AI-happy astrophysicists. And if you can’t do that, the talent pool becomes very small very quickly, since these machine learning techniques are so new and so different from standard software development. Even the big players talk about the tiny talent pool: Microsoft research chief Peter Lee says the cost of acquiring a top AI researcher is comparable to the cost of acquiring an NFL quarterback.
Over the past few years, other heavyweights have snapped up so many other AI startups you’ve never heard of. Twitter bought Mad Bits, Whetlab, and Magic Pony. Apple bagged Turi and Tuplejump. Salesforce acquired MetaMind and Prediction I/O. Intel acquired Nervana. And that’s just a partial list. And it’s not just software and Internet companies doing the buying. It’s also giants like Samsung and GE that are incorporating AI into physical things. As soon as startups spring up to meet the AI need, they get sucked up into the maws of the hungriest, richest corporations.
This is yet another example of how the concept of “corporate inequality” plays out in the market for talent. At organizations without the budget to hire “an NFL quarterback,” as it were, HR will have to find even more roundabout ways to get access to these in-demand specialists. Encouraging more students to pursue STEM education is a long-term strategy, but organizations will need AI skills sooner than that—and so, for that matter, will HR.
As an HR leader in the age of talent analytics, you need to consider not only how to attract experts in fields like AI, machine learning, and data science to your organization, but also how to get those specialists involved in your own analytics program. One way to achieve this is to develop cooperative relationships with other analytics professionals inside your company. CEB Corporate Leadership Council members can learn more about this from our case study of how Philips creates cross-functional HR analytics teams that leverage expertise from other teams or functions.